CACTUS: integrating clonal architecture with genomic clustering and transcriptome profiling of single tumor cells

Abstract Background Drawing genotype-to-phenotype maps in tumors is of paramount importance for understanding tumor heterogeneity.Assignment of single cells to their tumor clones of origin can be approached by matching the genotypes of the clones to the mutations found in RNA sequencing of the cells.The confidence of the cell-to-clone mapping can b

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Amundsen Sea Embayment ice-sheet mass-loss predictions to 2050 calibrated using observations of velocity and elevation change

Mass loss from the Amundsen Sea Embayment MENS BASIC TANKS of the West Antarctic Ice Sheet is a major contributor to global sea-level rise (SLR) and has been increasing over recent decades.Predictions of future SLR are increasingly modelled using ensembles of simulations within which model parameters and external forcings are varied within credible

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Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Identify ADHD and Autism.

A clinical tool that can diagnose psychiatric illness using functional Hair Clips or structural magnetic resonance (MR) brain images has the potential to greatly assist physicians and improve treatment efficacy.Working toward the goal of automated diagnosis, we propose an approach for automated classification of ADHD and autism based on histogram o

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Codifying unstructured data: A Natural Language Processing approach to extract rich data from clinical letters

ABSTRACT Objectives Electronic healthcare records (EHR) are the main data sources that facilitate epidemiology research.Routinely collected data such as primary and secondary care are now easily linked to produce novel and high impact research.There are, however, rich data locked in the free text of clinical letters that are not otherwise translate

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